Representational states in multi-item working memory

在日常生活中，人类需要在很短的时间内记住信息，并灵活地使用这些信息来做出决定和指导行为。这种能力被称为“工作记忆”。我们保存在工作记忆中的所有信息都是不平等的；有些信息可能比其他信息更相关。例如，当你离开家的时候，你可能会优先记住你的钥匙，而不是记住你以后需要在杂货店买的东西。有证据表明，我们可以灵活地将注意力分配到记忆中的项目上，从而使关注的项目对行为产生更大的影响。新的机器学习算法可以根据大脑活动模式解码记忆对象的特征(如位置或方向)，结果表明，记忆中的关注对象也比无人看管的对象解码得更好。在提出的DPhil项目中，我将使用一系列方法，包括人类行为(准确性和反应时间)、人类神经成像和猴子电生理学，来探索工作记忆中的多个项目是如何在大脑中呈现的。这些结果可能有助于为大脑系统如何实现复杂的思维和行为提供理论依据。BBSRC优先领域生物科学的系统方法脑科学和心理健康

In everyday life, humans need to keep information in mind over short periods of time and use this information flexibly to make decisions and guide behaviour. This ability is known as 'working memory'. Notall information we keep in working memory is equal; some information may be more relevant than the rest. For example, when leaving your house, you may prioritize remembering your keys over rememberingwhat items you need to buy at the grocery store later. There is evidence that we can flexibly allocate attention to items in memory thereby giving the attended items a stronger influence over behaviour.Novel machine learning algorithms that can decode features (e.g. location or orientation) of memorised objects from patterns of brain activity have shown that attended objects in memory are also betterdecoded than unattended objects. In the proposed DPhil project, I will use a range of methods including human behaviour (accuracy and reaction time), human neuroimaging, and monkey electrophysiology toexplore how multiple items in working memory are represented in the brain. The results may help inform theories of how brain systems achieve complex thought and behavior.BBSRC priority areasSystems approaches to the biosciencesBrain science and mental healthWUB, ENWW